Application of physiologically based pharmacokinetic modeling to predict drug disposition in pregnant populations.
Vamshi Krishna JogirajuSuvarchala AvvariRakesh GollenDavid R TaftPublished in: Biopharmaceutics & drug disposition (2017)
Pregnancy is associated with numerous physiological changes that influence absorption, distribution, metabolism and excretion. Moreover, the magnitude of these effects changes as pregnancy matures. For most medications, there is limited information available about changes in drug disposition that can occur in pregnant patients, yet most women are prescribed one or more medications during pregnancy. In this investigation, PBPK modeling was used to assess the impact of pregnancy on the pharmacokinetic profiles of three medications (metformin, tacrolimus, oseltamivir) using the Simcyp® simulator. The Simcyp pregnancy-PBPK model accounts for the known physiological changes that occur during pregnancy. For each medication, plasma concentration-time profiles were simulated using Simcyp® virtual populations of healthy volunteers and pregnant patients. The predicted systemic exposure metrics (Cmax , AUC) were compared with published clinical data, and the fold error (FE, ratio of predicted and observed data) was calculated. The PBPK model was able to capture the observed changes in Cmax and AUC across each trimester of pregnancy compared with post-partum for metformin (FE range 0.86-1.19), tacrolimus (FE range 1.03-1.64) and oseltamivir (FE range 0.54-1.02). Simcyp model outputs were used to correlate these findings with pregnancy-induced alterations in renal blood flow (metformin, oseltamivir), hepatic CYP3A4 activity (tacrolimus) and reduced plasma protein levels and hemodilution (tacrolimus). The results illustrate how PBPK modeling can help to establish appropriate dosing guidelines for pregnant patients and to predict potential changes in systemic exposure during pregnancy for compounds undergoing clinical development.
Keyphrases
- end stage renal disease
- pregnancy outcomes
- preterm birth
- ejection fraction
- chronic kidney disease
- pregnant women
- blood flow
- prognostic factors
- healthcare
- randomized controlled trial
- systematic review
- machine learning
- patient reported outcomes
- adipose tissue
- risk assessment
- skeletal muscle
- diabetic rats
- high glucose
- visible light